Automated AI Driven Interest Based Group Formation Workflow

Automated Interest-Based Group Formation

1. Data Collection

1.1 User Profile Creation

Users create profiles by providing personal information, interests, and preferences through an intuitive interface.

1.2 Interest Survey

Implement an AI-driven survey tool, such as Typeform or SurveyMonkey, to gather detailed insights on user interests and preferences.

2. Data Analysis

2.1 Interest Categorization

Utilize machine learning algorithms to categorize user interests into predefined groups. Tools like TensorFlow or IBM Watson can be used for this analysis.

2.2 Similarity Scoring

Apply AI algorithms to calculate similarity scores between users based on their interests, utilizing tools like Scikit-learn or RapidMiner.

3. Group Formation

3.1 Automated Matching

Leverage AI-driven matching systems to automatically group users with similar interests. Products like Bumble Bizz or Meetup can serve as models for this functionality.

3.2 Group Size Optimization

Implement an optimization algorithm to ensure groups are formed within ideal size parameters, enhancing user engagement and interaction.

4. Event Planning

4.1 Event Suggestion Engine

Utilize AI to recommend events based on group interests, using platforms like Eventbrite or Facebook Events for integration.

4.2 Scheduling and Coordination

Employ AI scheduling tools, such as Doodle or Calendly, to facilitate group availability and coordinate event logistics.

5. Feedback and Iteration

5.1 Post-Event Surveys

After events, deploy AI-driven feedback tools to gather user satisfaction data and insights, ensuring continuous improvement.

5.2 Data-Driven Adjustments

Analyze feedback using AI analytics tools, such as Google Analytics or Tableau, to refine group formation algorithms and enhance future user experiences.